Paper: https://arxiv.org/abs/2203.13448
Code: https://github.com/lijuncheng16/AudioTaggingDoneRight
For anyone who's interested in AudioSet (2million youtube videos' sound). This is the SOTA comparison of models and training procedures.
submitted by /u/billyli_16
[link] [comments]
submitted by /u/fasttosmile
[link] [comments]
Jonathan came on the Weaviate Podcast to discuss the story of MosaicML, their new open-source Python library for Efficient Deep Learning called Composer, Pareto Curves of Training Time X Accuracy, Model Surgey augmentations, Maximizing CPU and GPU throughput, and many more! I hope you find this useful, happy to continue discussions of what Jonathan presented!
https://www.youtube.com/watch?v=ZiBkspwrICA
submitted by /u/HenryAILabs
[link] [comments]
( 1
min )
submitted by /u/regalalgorithm
[link] [comments]
( 1
min )
submitted by /u/Nitorblog
[link] [comments]
( 1
min )
submitted by /u/TheNerdyDevYT
[link] [comments]
submitted by /u/sivasiriyapureddy
[link] [comments]
Google researchers created JAX to conduct NumPy computations on GPUs and TPUs. DeepMind uses it to help and expedite its research, and it is increasingly gaining popularity. Differentiation with grad(), vectorization with map(), and JIT-compilation (just-in-time) with jit are some of the composable functions required for machine learning research in JAX (). As a result, adding a JAX-based workload to the Flower code samples is a must-have. The combination of JAX and Flower allows ML and FL researchers to employ the deep learning framework that their projects demand. The updated code example now serves as a template for migrating existing JAX projects to a federated environment.
It’s pretty simple to put up a centralized machine learning architecture, and the JAX developer documentation has multiple examples. Because the ML model parameters are stored in the DeviceArray data format, setting up the federated workload requires some knowledge of JAX. To be compatible with the Flower NumPyClient, those arguments must be converted to NumPy ndarrays. The JAX meets Flower example below demonstrates how a Flower setup might work.
Continue Reading
submitted by /u/No_Coffee_4638
[link] [comments]
( 1
min )
submitted by /u/Illustrious_Row_9971
[link] [comments]
submitted by /u/aidev2040
[link] [comments]
Today, customers interact with brands over an increasingly large digital and offline footprint, generating a wealth of interaction data known as behavioral data. As a result, marketers and customer experience teams must work with multiple overlapping tools to engage and target those customers across touchpoints. This increases complexity, creates multiple views of each customer, and […]
( 10
min )
This is blog post is co-written by Theresa Cabrera Menard, an Applied Scientist/Geographic Information Systems Specialist at The Nature Conservancy (TNC) in Hawaii. In recent years, Amazon and AWS have developed a series of sustainability initiatives with the overall goal of helping preserve the natural environment. As part of these efforts, AWS Professional Services establishes […]
( 11
min )
Amazon SageMaker Autopilot helps you complete an end-to-end machine learning (ML) workflow by automating the steps of feature engineering, training, tuning, and deploying an ML model for inference. You provide SageMaker Autopilot with a tabular data set and a target attribute to predict. Then, SageMaker Autopilot automatically explores your data, trains, tunes, ranks and finds […]
( 10
min )
“I am a visionary,” says an AI, kicking off the latest installment of NVIDIA’s I AM AI video series. Launched in 2017, I AM AI has become the iconic opening for GTC keynote addresses by NVIDIA founder and CEO Jensen Huang. Each video, with its AI-created narration and soundtrack, documents the newest advances in artificial Read article >
The post Latest ‘I AM AI’ Video Features Four-Legged Robots, Smart Cell Analysis, Tumor-Tracking Tech and More appeared first on NVIDIA Blog.
( 3
min )
When Tanish Tyagi published his first research paper a year ago on deep learning to detect dementia, it started a family-driven pursuit. Great-grandparents in his family had suffered from Parkinson’s, a genetic disease that affects more than 10 million people worldwide. So the now 16-year-old turned to that next, together with his sister, Riya, 14. Read article >
The post Teens Develop Handwriting-Recognition AI for Detecting Parkinson’s Disease appeared first on NVIDIA Blog.
( 3
min )
Associate professor and principal investigator with the MIT Schwarzman College of Computing’s Science Hub discusses the future of robotics and the importance of industry-academia collaborations.
( 5
min )
MIT AI Hardware Program launches with five inaugural companies to advance AI technologies for the next decade.
( 5
min )
Inventory management is an essential part of any eCommerce business. Especially if you are an eCommerce business owner juggling multiple sales channels, it can save you a lot of effort. However, manually managing your inventories is also a recipe for error. Also, let’s not forget the time you have to spend and the painful process… Read More »Automated Inventory Management System: An Ultimate Guide for 2022 and Beyond
The post Automated Inventory Management System: An Ultimate Guide for 2022 and Beyond appeared first on Data Science Central.
( 5
min )
Statistics gives business owners the freedom to evaluate how their websites are performing. The evaluation involves a couple of things: the bounce rate and the exit rate. But what is the difference between bounce rate and exit rate? This is a point of discussion that requires you to have an open mind to grasp the… Read More »What is the Difference Between Bounce Rate and Exit Rate?
The post What is the Difference Between Bounce Rate and Exit Rate? appeared first on Data Science Central.
( 5
min )
There is no denying the importance of the internet and IT in the business scene. Businesses hailing from all sectors are dependent on the web, and they also make use of various types of software applications nowadays. However, with time, such technologies are also evolving. Businesses are coping with huge amounts of data, and to… Read More »Five Major Benefits That Microsoft Power BI Brings To Data Scientists
The post Five Major Benefits That Microsoft Power BI Brings To Data Scientists appeared first on Data Science Central.
( 5
min )
submitted by /u/kevinwangg
[link] [comments]
( 1
min )
submitted by /u/ML_Firefighter
[link] [comments]
submitted by /u/trcytony
[link] [comments]
( 1
min )
submitted by /u/MarS_0ne
[link] [comments]
submitted by /u/pmz
[link] [comments]
submitted by /u/sivasiriyapureddy
[link] [comments]
submitted by /u/satish_gaire
[link] [comments]
submitted by /u/kuasha7
[link] [comments]
submitted by /u/bendee983
[link] [comments]
submitted by /u/RubiksCodeNMZ
[link] [comments]
submitted by /u/Illustrious_Row_9971
[link] [comments]
( 1
min )
submitted by /u/Representative-Job23
[link] [comments]
https://github.com/minimaxir/imgbeddings
Instead, this package uses an ONNX INT8-quantized version of CLIP's Vision layers, which in testing works just as well, with a significant performance boost.
The demos also turned out very well, and try to a bit more fun than usual.
submitted by /u/minimaxir
[link] [comments]
( 1
min )
Vision Transformer Cookbook
Hello, I have released the Vision Transformer Cookbook with Tensorflow !
Therefore, you can easy to use the 22 transformer architectures via just copy & paste.
I hope this repository would help many people, including tensorflow users.
Thank you.
* code: vit-tensorflow
submitted by /u/taki0112
[link] [comments]
( 1
min )
submitted by /u/InfamousPancakes
[link] [comments]
( 2
min )
submitted by /u/djrobsmith
[link] [comments]
( 1
min )
It is common for growing organizations to reach a point where their existing data solution is no longer adequate for their needs. In most cases, it happens with companies that have used an on-premises infrastructure from the earliest days of business but now need to upgrade their network for continued growth. However, relocating equipment and… Read More »Datacenter relocation is now easier, faster, and more affordable
The post Datacenter relocation is now easier, faster, and more affordable appeared first on Data Science Central.
( 3
min )
“Privid” could help officials gather secure public health data or enable transportation departments to monitor the density and flow of pedestrians, without learning personal information about people.
( 6
min )
submitted by /u/RubiksCodeNMZ
[link] [comments]
One of the best known examples of GPT-3 for developers is the Github co-pilot Trained on billions of lines of public code, GitHub Copilot is more than autocomplete of code. GitHub Copilot is powered by Codex, the new AI system created by OpenAI. GitHub Copilot understands significantly more context than most code assistants. GitHub Copilot… Read More »GitHub Co-Pilot Alternatives: Can They Match the Functionality of Co-Pilot?
The post GitHub Co-Pilot Alternatives: Can They Match the Functionality of Co-Pilot? appeared first on Data Science Central.
( 3
min )
Despite the technological breakthroughs in the advent of Industry 4.0, manufacturers seem to have taken a more gradual approach to adoption. In 2020, less than 30 percent of the industry considered themselves extensive users of advanced integrated tools and processes. The pandemic, however, brought out an unprecedented need to explore opportunities that make manufacturing systems… Read More »Smart Maintenance – How SaaS Frameworks Turn Insights Into Actions Quickly And Efficiently
The post Smart Maintenance – How SaaS Frameworks Turn Insights Into Actions Quickly And Efficiently appeared first on Data Science Central.
( 5
min )
What is the toll-free number? Businesses provide a cloud-based contact number to allow customers to contact them free of cost. In India, this number- the business toll-free number is available in the 1800 series in an easily recognizable format- 1800-ABC-DEFG. Customers do not have to incur any fee to contact the business, as the company… Read More »Toll-free number: What is it, and how can you get one for your business?
The post Toll-free number: What is it, and how can you get one for your business? appeared first on Data Science Central.
( 4
min )
submitted by /u/Thenamessd
[link] [comments]
submitted by /u/qptbook
[link] [comments]
submitted by /u/the_embassy_official
[link] [comments]
( 1
min )
submitted by /u/sivasiriyapureddy
[link] [comments]
submitted by /u/HumanSeeing
[link] [comments]
( 2
min )
submitted by /u/pmz
[link] [comments]
submitted by /u/OnlyProggingForFun
[link] [comments]
( 1
min )
submitted by /u/Illustrious_Row_9971
[link] [comments]
( 1
min )
submitted by /u/zicxor
[link] [comments]
( 1
min )
submitted by /u/OnlyProggingForFun
[link] [comments]
submitted by /u/NarutoNotBoruto
[link] [comments]
Found a useful list of Tools and Programs for AI/ML. Looks like it covers Machine Learning, Deep Learning, Computer Vision(CV), and Natural Language Processing (NLP). I thought I'd share it for anyone that's interested. https://github.com/mikeroyal/Machine-Learning-Guide
submitted by /u/Khaotic_Kernel
[link] [comments]
submitted by /u/Recent_Coffee_2551
[link] [comments]
I thought it will be quite interesting to see Deep Convolutional GAN’s capability in generating wildlife, so I wrote a tutorial on how to build a model based on the DCGAN architecture through PyTorch:
https://taying-cheng.medium.com/create-new-animals-using-dcgan-with-pytorch-2ce47810ebd4
submitted by /u/Ok-Peanut-2681
[link] [comments]
submitted by /u/getrich_or_diemining
[link] [comments]
submitted by /u/Illustrious_Row_9971
[link] [comments]
( 1
min )
I recently wrote a critical review on "Deep Learning for Tabular Data" which reviews whether we are ready to move from Tree-based models to Neural Network-based models for Tabular data. It covers many novel approaches such as DeepInsight, IGTD and SuperTML. It also includes some of the transformers based recent works such as TabNet, Tab-Transformer, AutoInt, FT-Transformer and regularisation models such MLP+.
I have most commonly found the lack of a defined benchmark which makes it hard for people to find the right algorithms for the task. I am creating this discussion so that people who are using some of these algorithms or have tested some of them in different scenarios can share their findings.
submitted by /u/Raghuvansh_Tahlan
[link] [comments]
( 1
min )
This post is co-written by Shibangi Saha, Data Scientist, and Graciela Kravtzov, Co-Founder and CTO, of Equilibrium Point. Many individuals are experiencing new symptoms of mental illness, such as stress, anxiety, depression, substance use, and post-traumatic stress disorder (PTSD). According to Kaiser Family Foundation, about half of adults (47%) nationwide have reported negative mental health […]
( 8
min )
Amazon Kendra is an intelligent search service powered by machine learning. You can receive spelling suggestions for misspelled terms in your queries by utilizing the Amazon Kendra Spell Checker. Spell Checker helps reduce the frequency of queries returning irrelevant results by providing spelling suggestions for unrecognized terms. In this post, we explore how to use […]
( 4
min )
submitted by /u/data-gig
[link] [comments]
submitted by /u/snoggel
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/PM_ME_YOUR_PC_DEALS
[link] [comments]
submitted by /u/OnlyProggingForFun
[link] [comments]
( 1
min )
submitted by /u/gwern
[link] [comments]
( 1
min )
When the first instant photo was taken 75 years ago with a Polaroid camera, it was groundbreaking to rapidly capture the 3D world in a realistic 2D image. Today, AI researchers are working on the opposite: turning a collection of still images into a digital 3D scene in a matter of seconds. Known as inverse Read article >
The post NVIDIA Research Turns 2D Photos Into 3D Scenes in the Blink of an AI appeared first on NVIDIA Blog.
( 4
min )
submitted by /u/regalalgorithm
[link] [comments]
submitted by /u/regalalgorithm
[link] [comments]
submitted by /u/sivasiriyapureddy
[link] [comments]
submitted by /u/Recent_Coffee_2551
[link] [comments]
submitted by /u/Puzzleheaded-Gas-906
[link] [comments]
submitted by /u/FurryMachine
[link] [comments]
GeForce NOW gives you the power to game almost anywhere, at GeForce quality. And with the latest controller from SteelSeries, members can stay in control of the action on Android and Chromebook devices. This GFN Thursday takes a look at the SteelSeries Stratus+, now part of the GeForce NOW Recommended program. And it wouldn’t be Read article >
The post Take Control This GFN Thursday With New Stratus+ Controller From SteelSeries appeared first on NVIDIA Blog.
( 3
min )
The hum of a bustling data center is music to an AI developer’s ears — and NVIDIA data centers have found a rhythm of their own, grooving to the swing classic “Sing, Sing, Sing” in this week’s GTC keynote address. The lighthearted video, created with the NVIDIA Omniverse platform, features Louis Prima’s iconic music track, Read article >
The post Orchestrated to Perfection: NVIDIA Data Center Grooves to Tune of Millionfold Speedups appeared first on NVIDIA Blog.
( 4
min )
Introduction Splunk is a well-known log management tool. Splunk mines log from different machines in real-time and can be used to monitor, search, and analyze gathered data. It is a Big Data log management tool that can give insight from the unstructured data stored in the Splunk indexes. Splunk analytics helps turn unstructured log data… Read More »Business Analytics from Application Logs and Database using Splunk
The post Business Analytics from Application Logs and Database using Splunk appeared first on Data Science Central.
( 11
min )
submitted by /u/gwern
[link] [comments]
I was reading this post about the TRPO algorithm. But I couldn't understand how we use MM algorithm in TRPO. I also watched some videos, they talked something about maximizing lower bound but I am not able to catch up what they are explaining. Can anyone explain this to me?
submitted by /u/Better-Ad8608
[link] [comments]
( 1
min )
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/nonaime7777777
[link] [comments]
The previous post covered the problem of oversiloing. Systems thinking, I pointed out, can help reduce the practice of siloing when it’s not necessary. In earlier posts, I’ve contrasted the difference between provincial IT and data-centric IT: Provincial IT is no longer necessary given the advances in compute, networking and storage we’ve seen over the… Read More »The long game: Feedback loops and desiloed systems by design (Part II of II)
The post The long game: Feedback loops and desiloed systems by design (Part II of II) appeared first on Data Science Central.
( 5
min )
When OpenAI released the third generation of their machine learning (ML) model that specializes in text generation in July 2020, I knew something was different. This model struck a nerve like no one that came before it. Suddenly I heard friends and colleagues, who might be interested in technology but usually don’t care much about […]
( 10
min )
This is a guest post co-authored by Taylor Names, Staff Machine Learning Engineer, Dev Gupta, Machine Learning Manager, and Argie Angeleas, Senior Product Manager at Ibotta. Ibotta is an American technology company that enables users with its desktop and mobile apps to earn cash back on in-store, mobile app, and online purchases with receipt submission, […]
( 7
min )
Autonomous vehicle development and validation require the ability to replicate real-world scenarios in simulation. At GTC, NVIDIA founder and CEO Jensen Huang showcased new AI-based tools for NVIDIA DRIVE Sim that accurately reconstruct and modify actual driving scenarios. These tools are enabled by breakthroughs from NVIDIA Research that leverage technologies such as NVIDIA Omniverse platform Read article >
The post NVIDIA Showcases Novel AI Tools in DRIVE Sim to Advance Autonomous Vehicle Development appeared first on NVIDIA Blog.
( 4
min )
This week at GTC, we’re celebrating – celebrating the amazing and impactful work that developers and startups are doing around the world. Nowhere is that more apparent than among the members of our global NVIDIA Inception program, designed to nurture cutting-edge startups who are revolutionizing industries. The program is free for startups of all sizes Read article >
The post NVIDIA Inception Introduces New and Updated Benefits for Startup Members to Accelerate Computing appeared first on NVIDIA Blog.
( 3
min )
The use of AI to write creative stories is increasing in popularity.
( 3
min )
Introduction/ Problem Splunk is a well-known log management tool. Splunk mines log from different machines in real-time and can be used to monitor, search, and analyze gathered data. It is a Big Data log management tool that can give insight from the unstructured data stored in the Splunk indexes. Splunk analytics helps turn unstructured log… Read More »Business Analytics from Application Logs and SQL Server Database using Splunk
The post Business Analytics from Application Logs and SQL Server Database using Splunk appeared first on Data Science Central.
( 11
min )
In many cases, for an enterprise to build its digital business technology platform, it must modernize its traditional data and analytics architecture. A modern data and analytics platform should be built on services-based principles and architecture. Introduction part 1, provided a conceptual-level reference architecture of a traditional Data and Analytics (D&A) platform. This part, provides… Read More »How to Modernize Enterprise Data and Analytics Platform (Part 2 of 4)
The post How to Modernize Enterprise Data and Analytics Platform (Part 2 of 4) appeared first on Data Science Central.
( 16
min )
AI has been making its way into the marketing world over the last few years. Businesses have touted it as the solution to their problems and a way to incorporate technology into their processes. But, how is AI changing SEO? How can you use AI to improve your business? Machine learning and artificial intelligence are… Read More »AI SEO: How AI Helps You Optimize Content for Search Results
The post AI SEO: How AI Helps You Optimize Content for Search Results appeared first on Data Science Central.
( 4
min )
Every time we think we have grasped a new technology and its use. Sometimes that shift is an increase in the technology itself that seemingly intensifies the original version. Sometimes something happens that causes a significant transformation in the technology’s nature. As the technology’s significance is increasingly understood, the name is altered to better reflect… Read More »Understanding the Role of Augmented Data Catalogs in Data Governance
The post Understanding the Role of Augmented Data Catalogs in Data Governance appeared first on Data Science Central.
( 4
min )
This post was co-written by John Heater, SVP of the Contact Center Practice at NeuraFlash. NeuraFlash is an Advanced AWS Partner with over 40 collective years of experience in the voice and automation space. With a dedicated team of conversation designers, data engineers, and AWS developers, NeuraFlash helps customers take advantage of the power of Amazon […]
( 9
min )
Amazon Search’s vision is to enable customers to search effortlessly. Our spelling correction helps you find what you want even if you don’t know the exact spelling of the intended words. In the past, we used classical machine learning (ML) algorithms with manual feature engineering for spelling correction. To make the next generational leap in […]
( 7
min )
https://arxiv.org/abs/2203.10977
submitted by /u/gaggi_94
[link] [comments]
We're happy to announce the release of STUMPY v1.11.0! This version includes the oft requested Minkowski (p-norm) Distance, support for Multi-dimensional Motif Discovery, new Annotation vector tutorials, and enhancements for Pan Matrix Profiles!
https://github.com/TDAmeritrade/stumpy
submitted by /u/slaw07
[link] [comments]
( 1
min )
FDG2022: Foundations of Digital Games 2022Athens, Greece, September 5-8, 2022Conference website: http://fdg2022.org/
Foundations of Digital Games (FDG) 2022 invites research contributions in the form of papers, posters and demos, doctoral consortium applications, as well as panel, competition, and workshop proposals.
We invite contributions from within and across any discipline committed to advancing knowledge on the foundations of games: computer science and engineering, humanities and social sciences, arts and design, mathematics and natural sciences. As was the case in the previous years, we aim to publish the FDG 2022 proceedings in the ACM Digital Library. FDG invites authors to submit short or full papers reporting new research. Both short and full papers need to be anonymized and…
( 1
min )
Hi!
I have some experience deploying batch machine learning models and now I want to learn about real-time models. More specifically, how to put them in production and what are the best practices and tools for different use-cases.
Any ideas? I was thinking of reading the book "Designing Event-Driven Systems" by Ben Stopford (I think it's based on Kafka which seems quite popular), but would like to hear your thoughts or if someone has any other reference.
Thanks and I hope this is the right sub!
submitted by /u/Silver_Book_938
[link] [comments]
( 1
min )
submitted by /u/thedyezwfl
[link] [comments]
( 1
min )
Generative Adversarial Networks (GANs), with their capacity of producing high-quality images, have been the leading technology in image generation for the past couple of years. Nevertheless, their minimax learning mechanism brought out different limits, such as training instability and mode collapse (i.e., when all the produced samples belong to a small set of samples).
Recently, Generative Transformer models are beginning to match, or even surpass, the performances of GANs. The simple idea is to learn a function to encode the input image into a quantized sequence and then train an autoregressive Transformer on a sequence prediction task (i.e., predict an image token, given all the previous image tokens). This learning is based on maximum likelihood and thus not affected by the same issue…
( 2
min )
submitted by /u/nonaime7777777
[link] [comments]
submitted by /u/nonaime7777777
[link] [comments]
submitted by /u/getrich_or_diemining
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/sopadebombillas
[link] [comments]
submitted by /u/VikasOjha666
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/sivasiriyapureddy
[link] [comments]
submitted by /u/trcytony
[link] [comments]
( 1
min )
At GTC, NVIDIA announced significant updates for millions of creators using the NVIDIA Omniverse real-time 3D design collaboration platform. The announcements kicked off with updates to the Omniverse apps Create, Machinima and Showroom, with an immement View release. Powered by GeForce RTX and NVIDIA RTX GPUs, they dramatically accelerate 3D creative workflows. New Omniverse Connections Read article >
The post NVIDIA Omniverse Upgrade Delivers Extraordinary Benefits to 3D Content Creators appeared first on NVIDIA Blog.
( 5
min )
Digital artists and creative professionals have plenty to be excited about at NVIDIA GTC. Impressive NVIDIA Studio laptop offerings from ASUS and MSI launch with upgraded RTX GPUs, providing more options for professional content creators to elevate and expand creative possibilities. NVIDIA Omniverse gets a significant upgrade — including updates to the Omniverse Create, Machinima Read article >
The post At GTC: NVIDIA RTX Professional Laptop GPUs Debut, New NVIDIA Studio Laptops, a Massive Omniverse Upgrade and NVIDIA Canvas Update appeared first on NVIDIA Blog.
( 6
min )
Promising to transform trillion-dollar industries and address the “grand challenges” of our time, NVIDIA founder and CEO Jensen Huang Tuesday shared a vision of an era where intelligence is created on an industrial scale and woven into real and virtual worlds. Kicking off NVIDIA’s GTC conference, Huang introduced new silicon — including the new Hopper Read article >
The post Keynote Wrap Up: Turning Data Centers into ‘AI Factories,’ NVIDIA CEO Intros Hopper Architecture, H100 GPU, New Supercomputers, Software appeared first on NVIDIA Blog.
( 8
min )
The University of Florida’s academic health center, UF Health, has teamed up with NVIDIA to develop a neural network that generates synthetic clinical data — a powerful resource that researchers can use to train other AI models in healthcare. Trained on a decade of data representing more than 2 million patients, SynGatorTron is a language Read article >
The post Unlimited Data, Unlimited Possibilities: UF Health and NVIDIA Build World’s Largest Clinical Language Generator appeared first on NVIDIA Blog.
( 4
min )
Remote work and hybrid workplaces are the new normal for professionals in many industries. Teams spread throughout the world are expected to create and collaborate while maintaining top productivity and performance. Businesses use the NVIDIA RTX platform to enable their workers to keep up with the most demanding workloads, from anywhere. And today, NVIDIA is Read article >
The post New NVIDIA RTX GPUs Tackle Demanding Professional Workflows and Hybrid Work, Enabling Creation From Anywhere appeared first on NVIDIA Blog.
( 4
min )
Four NVIDIA Inception members have been selected as the first cohort of startups to access Cambridge-1, the U.K.’s most powerful supercomputer. The system will help British companies Alchemab Therapeutics, InstaDeep, Peptone and Relation Therapeutics enable breakthroughs in digital biology. Officially launched in July, Cambridge-1 — an NVIDIA DGX SuperPOD cluster powered by NVIDIA DGX A100 Read article >
The post First Wave of Startups Harnesses UK’s Most Powerful Supercomputer to Power Digital Biology Breakthroughs appeared first on NVIDIA Blog.
( 4
min )
When it comes to creating and connecting virtual worlds, over 150,000 individuals have downloaded NVIDIA Omniverse to make huge leaps in transforming 3D design workflows and achieve new heights of real-time, physically accurate simulations. At GTC, NVIDIA today announced new releases and updates for Omniverse — including the latest Omniverse Connectors and libraries — expanding Read article >
The post NVIDIA Omniverse Ecosystem Expands 10x, Amid New Features and Services for Developers, Enterprises and Creators appeared first on NVIDIA Blog.
( 4
min )
Next time socks, cereal or sandpaper shows up in hours delivered to your doorstep, consider the behind-the-scenes logistics acrobatics that help get them there so fast. Order fulfillment is a massive industry of moving parts. Heavily supported by autonomous mobile robots (AMRs), warehouses can span 1 million square feet, expanding and reconfiguring to meet demands. Read article >
The post NVIDIA Unveils Isaac Nova Orin to Accelerate Development of Autonomous Mobile Robots appeared first on NVIDIA Blog.
( 3
min )
Lucid Group may be a newcomer to the electric vehicle market, but its entrance has been grand. The electric automaker announced at GTC that its current and future fleets are built on NVIDIA DRIVE Hyperion for programmable, intelligent capabilities. By developing on the scalable, software-defined platform, Lucid ensures its vehicles are always at the cutting Read article >
The post Driving on Air: Lucid Group Builds Intelligent EVs on NVIDIA DRIVE appeared first on NVIDIA Blog.
( 2
min )
NVIDIA DRIVE Hyperion and DRIVE Orin are gaining ground in the industry. At NVIDIA GTC, BYD, the world’s second-largest electric vehicle maker, announced it is building its next-generation fleets on the DRIVE Hyperion architecture. This platform, based on DRIVE Orin, is now in production, and powering a wide ecosystem of 25 EV makers building software-defined Read article >
The post NVIDIA DRIVE Continues Industry Momentum With $11 Billion Pipeline as DRIVE Orin Enters Production appeared first on NVIDIA Blog.
( 3
min )
With a detailed knowledge of the world and everything in it, maps provide the foresight AI uses to make advanced and safe driving decisions. At his GTC keynote, NVIDIA founder and CEO Jensen Huang introduced NVIDIA DRIVE Map, a multimodal mapping platform designed to enable the highest levels of autonomy while improving safety. It combines Read article >
The post Announcing NVIDIA DRIVE Map: Scalable, Multi-Modal Mapping Engine Accelerates Deployment of Level 3 and Level 4 Autonomy appeared first on NVIDIA Blog.
( 4
min )
NVIDIA DRIVE Hyperion is taking software-defined vehicle architectures to the next level. At his GTC keynote, NVIDIA founder and CEO Jensen Huang announced DRIVE Hyperion 9, the next generation of the open platform for automated and autonomous vehicles. The programmable architecture, slated for 2026 production vehicles, is built on multiple DRIVE Atlan computers to achieve Read article >
The post Introducing NVIDIA DRIVE Hyperion 9: Next-Generation Platform for Software-Defined Autonomous Vehicle Fleets appeared first on NVIDIA Blog.
( 3
min )
Siemens Gamesa Renewable Energy is working with NVIDIA to create physics-informed digital twins of wind farms — groups of wind turbines used to produce electricity. The company has thousands of turbines around the globe that light up schools, homes, hospitals and factories with clean energy. In total they generate over 100 gigawatts of wind power, Read article >
The post Siemens Gamesa Taps NVIDIA Digital Twin Platform for Scientific Computing to Accelerate Clean Energy Transition appeared first on NVIDIA Blog.
( 3
min )
AT&T’s wireless network connects more than 100 million subscribers from the Aleutian Islands to the Florida Keys, spawning a big data sea. Abhay Dabholkar runs a research group that acts like a lighthouse on the lookout for the best tools to navigate it. “It’s fun, we get to play with new tools that can make Read article >
The post Speed Dialer: How AT&T Rings Up New Opportunities With Data Science appeared first on NVIDIA Blog.
( 3
min )
The NVIDIA Hopper GPU architecture unveiled today at GTC will accelerate dynamic programming — a problem-solving technique used in algorithms for genomics, quantum computing, route optimization and more — by up to 40x with new DPX instructions. An instruction set built into NVIDIA H100 GPUs, DPX will help developers write code to achieve speedups on Read article >
The post NVIDIA Hopper GPU Architecture Accelerates Dynamic Programming Up to 40x Using New DPX Instructions appeared first on NVIDIA Blog.
( 3
min )
The largest AI models can require months to train on today’s computing platforms. That’s too slow for businesses. AI, high performance computing and data analytics are growing in complexity with some models, like large language ones, reaching trillions of parameters. The NVIDIA Hopper architecture is built from the ground up to accelerate these next-generation AI Read article >
The post H100 Transformer Engine Supercharges AI Training, Delivering Up to 6x Higher Performance Without Losing Accuracy appeared first on NVIDIA Blog.
( 4
min )
Everyone wants to be heard. And with more people than ever in video calls or live streaming from their home offices, rich audio free from echo hiccups and background noises like barking dogs is key to better sounding online experiences. NVIDIA Maxine offers GPU-accelerated, AI-enabled software development kits to help developers build scalable, low-latency audio Read article >
The post NVIDIA Maxine Reinvents Real-Time Communication With AI appeared first on NVIDIA Blog.
( 5
min )
submitted by /u/hotcodist
[link] [comments]
Using the Artificial Neural Network (ANN) to make a churn model, we will create a model that predicts a handwritten digit. (with source…
( 3
min )
submitted by /u/kuasha7
[link] [comments]
submitted by /u/regalalgorithm
[link] [comments]
( 1
min )
submitted by /u/bendee983
[link] [comments]
submitted by /u/bent_out_of_shape_
[link] [comments]
submitted by /u/VIRUS-AOTOXIN
[link] [comments]
submitted by /u/RubiksCodeNMZ
[link] [comments]
submitted by /u/dannylenwinn
[link] [comments]
( 1
min )
Researchers from LinkedIn open-source the FastTreeSHAP package which is a Python module based on the paper ‘Fast TreeSHAP: Accelerating SHAP Value Computation for Trees.’ Implementing the widely-used TreeSHAP algorithm in the SHAP package allows for the efficient interpretation of tree-based machine learning models by estimating sample-level feature significance values. Its package includes two new algorithms: FastTreeSHAP v1 and FastTreeSHAP v2, both of which improve TreeSHAP’s computational efficiency by taking a different approach.
The empirical benchmarking tests show that FastTreeSHAP v1 is 1.5x faster than TreeSHAP while keeping memory costs the same, and FastTreeSHAP v2 is 2.5x faster while using slightly more memory. The FastTreeSHAP package fully supports parallel multi-core computing to speed up its computation.
Continue Reading The Full Summary Article
Paper: https://arxiv.org/pdf/2109.09847.pdf
Github: https://github.com/linkedin/fasttreeshap
submitted by /u/No_Coffee_4638
[link] [comments]
( 1
min )
I asked this question on stats stackexchange, and it is posted here. I don't copy it here because formulas don't show up nicely on reddit.
I am trying to implement this paper by Fallah et al (NIPs 2021) titled: On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning. As the title suggests, they propose an algorithm for meta RL that uses an stochastic approximation of the gradient. My problem is with the term that yields the probability of a given trajectory (a sequence of state-actions). I don't know how to estimate that term and the paper doesn't discuss that. I'd appreciate if anyone can share any insight on how to estimate that term.
submitted by /u/carlml
[link] [comments]
( 1
min )
I have made an animated video (https://www.youtube.com/watch?v=Rl-sFaE1z4M) for our ICLR 2022 paper (https://arxiv.org/abs/2203.09630).
Check it out if you are interested. I have made the video using 3b1b's manim library (https://github.com/ManimCommunity/manim).
Feedback is always very welcome!
submitted by /u/Human-Career-9962
[link] [comments]
( 1
min )
LinkedIn open sources the FastTreeSHAP Python package for efficient interpretation of tree-based ML models (XGBoost, LightGBM, sklearn random forest) using SHAPLEY. FastTreeSHAP v2 would be 2.5x faster than TreeSHAP. Let's reminder that SHAP (SHapley Additive exPlanation) values quantify the contribution of each feature to the model prediction, a bit like how each player contributes to the success of a sports team. SHAP does it by incorporating concepts from game theory and local explanations. Naively implemented, SHAP takes exponential time. LinkedIn blog post, scientific paper, and GitHub repo with IPython Notebooks.
submitted by /u/ClaudeCoulombe
[link] [comments]
( 1
min )
An author interview on the Equivariant Subgraph Aggregation Networks paper. Discusses why the expressive power of GNNs is limited and a method for breaking the bottleneck of the 1-WL algorithm
https://youtu.be/VYZog7kbXks
submitted by /u/zjost85
[link] [comments]
submitted by /u/stepanmetior
[link] [comments]
( 1
min )
submitted by /u/gwern
[link] [comments]
( 1
min )
submitted by /u/gwern
[link] [comments]
( 1
min )
submitted by /u/gwern
[link] [comments]
( 1
min )
submitted by /u/stepanmetior
[link] [comments]
( 1
min )
submitted by /u/mr-minion
[link] [comments]
( 1
min )
submitted by /u/RubiksCodeNMZ
[link] [comments]
The field of Artificial Intelligence (AI) continues to expand and improve by leaps and bounds. Today’s AI applications are becoming smarter…
( 3
min )
Figure 1: Airmass measurements over Ukraine from February 18, 2022 - March 01, 2022 from the SEVIRI instrument. Data accessed via the EUMETSAT Viewer.
Satellite imagery is a critical source of information during the current invasion of Ukraine. Military strategists, journalists, and researchers use this imagery to make decisions, unveil violations of international agreements, and inform the public of the stark realities of war. With Ukraine experiencing a large amount of cloud cover and attacks often occuring during night-time, many forms of satellite imagery are hindered from seeing the ground. Synthetic aperture radar imagery penetrates cloud cover, but requires special training to interpret. Automating this tedious task would enable real-time insights, but current computer vision meth…
( 11
min )
submitted by /u/Illustrious_Row_9971
[link] [comments]
( 1
min )
submitted by /u/pinter69
[link] [comments]
( 2
min )
Does RepL4NLP accept papers such as pruning and quantization? The link below gives you a list of topics if you scroll down. One of them was " Efficient learning of representations and inference: with respect to training and inference time, model size, amount of training data, etc.". I was wondering if that has anything to do with pruning and/or quantization?
https://sites.google.com/view/repl4nlp2022/
submitted by /u/SiegeMemeLord
[link] [comments]
( 1
min )
submitted by /u/OnlyProggingForFun
[link] [comments]
( 1
min )
submitted by /u/Representative-Job23
[link] [comments]
Seamless. Frictionless. Elegant. Efficient.
Read More
The post Building An Effective Experimentation Program – 01 Introduction appeared first on ML in Production.
( 4
min )
Seamless. Frictionless. Elegant. Efficient.
Read More
The post Building An Effective Experimentation Program – 01 Introduction appeared first on ML in Production.
( 4
min )
submitted by /u/Illustrious_Row_9971
[link] [comments]
Hello everyone!
I’ve recently read Swin Transformer paper and tried to implement with PyTorch. But there’re no post that FULLY explains the nitty-gritty details of the paper with full implementation. It took me soooo long time to write this post so I wanted to share with y’all! Hope this helps someone! The implementation is based on the official implementation of Microsoft team.
https://jasonlee-cp.github.io/paper/Swin_Transformer/#swin-transformer-architecture
submitted by /u/JasonTheCoders
[link] [comments]
( 1
min )
You can find the paper here:
https://arxiv.org/abs/2201.11870
And the code and the data here:
https://github.com/p-karisani/CEPC
submitted by /u/payam_ka
[link] [comments]
submitted by /u/toxickettle
[link] [comments]
( 3
min )
submitted by /u/covertBehavior
[link] [comments]
( 2
min )
submitted by /u/gwern
[link] [comments]
submitted by /u/Jazmineco
[link] [comments]
submitted by /u/Thenamessd
[link] [comments]
submitted by /u/Pale-Information3077
[link] [comments]
submitted by /u/Hacknaut
[link] [comments]
submitted by /u/notrealAI
[link] [comments]
( 1
min )
submitted by /u/amin_mlm
[link] [comments]
( 1
min )
submitted by /u/bperki8
[link] [comments]
Look for more info at: https://stackoverflow.com/questions/71533736/neural-network-is-training-to-give-just-one-output-how-can-i-prevent-this
submitted by /u/UnityPlum
[link] [comments]
submitted by /u/allaboutcircuits
[link] [comments]
submitted by /u/glenniszen
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
( 1
min )
A project supported by the STFC Hartree Centre Discovery Accelerator accurately predicts patient response to treatments for ulcerative colitis and Crohn’s disease.
Artificial intelligence may soon assist more than 6 million1 individuals worldwide who suffer from inflammatory bowel disease (IBD) in selecting the optimum medication for their illness. An explainable AI pharmacogenomics methodology we created effectively predicted how patients will respond — favorably or negatively — to an IBD treatment 95% of the time, according to research published in PLOSone.
Chronic inflammatory bowel diseases (IBDs) such as ulcerative colitis and Crohn’s disease are caused by clinical, genetic, and environmental variables such as nutrition and lifestyle. Even though all patients have the same symptoms, there is no one-size-fits-all treatment for IBD that is helpful for everybody. Choosing the optimum therapy for a patient is still a trial-and-error procedure for both the doctor and the patient.
According to researchers at IBM Research in the UK and REPROCELL, a stem cell and fresh tissue research firm, used IBD patient data and explainable AI approaches to study treatment reactions with the help of the STFC Hartree Centre’s Discovery Accelerator. Their objective was to discover the optimum medications for IBD therapies less of a guessing game. The resulting collection of algorithms demonstrated that it was feasible to crack the IBD data black box and comprehend forecast and explain how persons with IBD could react to different medications on the market and under development.
Continue Reading Our Research Summary
Paper: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0263248
submitted by /u/No_Coffee_4638
[link] [comments]
( 1
min )
submitted by /u/Thenamessd
[link] [comments]
Hello, we are publishing our first paper as undergraduate students today. It is achieving SOTA on the BDD100K dataset (2 out of 3 tasks, at least).
Paper: https://arxiv.org/abs/2203.09035
Code: https://github.com/datvuthanh/HybridNets
Network architecture:
HybridNets architecture
Contributions:
HybridNets, an end-to-end perception network, achieving outstanding results in real-time on the BDD100K dataset for 3 tasks: traffic object detection, drivable area segmentation (not SOTA), and lane line detection.
Automatically customized anchor for each level in the weighted bidirectional feature network, on any dataset.
An efficient training loss function and training strategy to balance and optimize multi-task networks.
submitted by /u/xoiga123
[link] [comments]
( 1
min )
Conversational AI can deliver powerful, automated, interactive experiences through voice and text. Amazon Lex is a service that combines automatic speech recognition and natural language understanding technologies, so you can build these sophisticated conversational experiences. A common application of conversational AI is found in contact centers: self-service virtual agents. We’re excited to announce that you […]
( 9
min )
AI Weirdness: the strange side of machine learning
( 1
min )
NVIDIA’s GTC conference is packed with smart people and programming. The virtual gathering — which takes place from March 21-24 — sits at the intersection of some of the fastest-moving technologies of our time. It features a lineup of speakers from every corner of industry, academia and research who are ready to paint a high-definition Read article >
The post Hopped Up: NVIDIA CEO, AI Leaders to Discuss Next Wave of AI at GTC appeared first on NVIDIA Blog.
( 3
min )
Deepspeed? FSDP? FFCV? XYZK? what do they all mean and how can you use all of them to speed up your model training? All amazing techniques developed by world-class teams and are (or are being made) accessible via PyTorch Lightning!
If you know of other techniques you want to be integrated, please comment below!
https://william-falcon.medium.com/pytorch-lightning-vs-deepspeed-vs-fsdp-vs-ffcv-vs-e0d6b2a95719
submitted by /u/waf04
[link] [comments]
( 1
min )
submitted by /u/regalalgorithm
[link] [comments]
submitted by /u/bendee983
[link] [comments]
( 1
min )
Hello,
Text processing AI has made great progress these last years but the main focus is on the English language (understandably). I think that many people are trying to do Natural Language Processing in non-English languages but are disappointed by the results. It is especially hard with text generation models like GPT-3, GPT-J, GPT-NeoX...
In this article, I'm trying to quickly summarize what the options are today for people trying to use a multilingual AI:
https://nlpcloud.io/multilingual-nlp-how-to-perform-nlp-in-non-english-languages.html
If you can think of additional solutions not mentioned in this article please let me know!
submitted by /u/juliensalinas
[link] [comments]
( 1
min )
submitted by /u/Thenamessd
[link] [comments]
A promising family of generative models has emerged: score-based generative models (SGMs) and denoising diffusion probabilistic models. SGMs have applications in image, voice, and music synthesis, image editing, super-resolution, image-to-image translation, and 3D shape generation because they provide high-quality synthesis and sample variety without requiring adversarial aims.
SGMs use a diffusion process to progressively introduce noise to the data, changing a complicated data distribution into a tractable prior distribution for analysis. The modified data’s score function—the gradient of the log probability density—is then learned using a neural network. To synthesize new samples, the learned scores can be used to solve a stochastic differential equation (SDE). Inverting the forward diffusion corresponds to an iterative denoising process.
Continue Reading
Paper: https://arxiv.org/pdf/2112.07068.pdf
Project: https://nv-tlabs.github.io/CLD-SGM/
Code: https://github.com/nv-tlabs/CLD-SGM
https://i.redd.it/8dl9ftuquzn81.gif
submitted by /u/No_Coffee_4638
[link] [comments]
( 1
min )
Organizational forms serve as a primary business tool across industries—from financial services, to healthcare, and more. Consider, for example, tax filing forms in the tax management industry, where new forms come out each year with largely the same information. AWS customers across sectors need to process and store information in forms as part of their […]
( 6
min )
CSAIL scientists came up with a learning pipeline for the four-legged robot that learns to run entirely by trial and error in simulation.
( 5
min )
The AI-Guided Ultrasound Intervention Device is a lifesaving technology that helps a range of users deliver complex medical interventions at the point of injury.
( 7
min )
submitted by /u/gwern
[link] [comments]
( 1
min )
submitted by /u/gwern
[link] [comments]
( 1
min )
These are my favorite free Datacamp courses to learn in-demand data skills like Python, SQL, Power BI, Tableau, Seaborn, Matplotlib, Data…
( 5
min )
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/HotMomentumStocks
[link] [comments]
submitted by /u/moinnadeem
[link] [comments]
( 1
min )
submitted by /u/regalalgorithm
[link] [comments]
( 1
min )
submitted by /u/Im_Will_Smith
[link] [comments]
submitted by /u/sivasiriyapureddy
[link] [comments]
submitted by /u/qptbook
[link] [comments]
( 1
min )
submitted by /u/kuasha7
[link] [comments]
submitted by /u/MLtinkerer
[link] [comments]
( 1
min )
submitted by /u/Beautiful-Credit-868
[link] [comments]
https://venturebeat.com/2021/11/15/astera-labs-announces-memory-acceleration-to-clear-datacenter-ai-ml-bottlenecks/
Do you think this technology would allow the use of clusters to handle larger data sets, thus reducing the overall cost of doing ML?
submitted by /u/sawine
[link] [comments]
( 1
min )
https://medium.com/p/306fa7b7a80b
I believe a common misconception is that you only need to apply MLOps principles and tools if you are running hundreds of models. I'd argue it's not less important in a lot earlier stages of the model lifecycle.
submitted by /u/stiebels
[link] [comments]
( 1
min )
The [BigScience project](https://bigscience.huggingface.co) has just started the training of its main model and the training can be followed live here: https://twitter.com/BigScienceLLM and here: https://huggingface.co/bigscience/tr11-176B-ml-logs/tensorboard#scalars&tagFilter=loss
Here are more information on the model, dataset, engineering, training and hardware:
The model:
176B parameters decoder-only architecture (GPT-like)
70 layers - 112 attention heads per layers - hidden dimensionality of 14336 - 2048 tokens sequence length
ALiBi positional embeddings - GeLU activation function
Read more:
Blog post summarizing how the architecture, size, shape, and pre-training duration where selected: https://bigscience.huggingface.co/blog/what-language-model-to-train-if-you-have-two-…
( 2
min )
In this video, I discuss ORQA which uses a retriever to find the right context from the entire Wikipedia and then uses an extractive QA model to give a final answer. We discuss the task setup, architecture, and loss function.
The video is part of 8 video series on Open domain question answering, how it is different from normal QA, the difference in loss formulations, and key papers on different Open-QA architectures.
I will really appreciate any feedback.
https://www.youtube.com/watch?v=9bL2VbwZ9G8
submitted by /u/infiniteakashe
[link] [comments]
( 1
min )
Hi MachineLearning,
I would like to introduce a new concept of utilizing factorized optical flow maps as mid-level representations, for bridging the perception and the control modules in modular learning based robotic frameworks.
In the below video, we demonstrate the DRL agent is able to control itself by perceiving the factorized optical flow maps, and without bumping into the pedestrians in the urban environment based on Unity.
Hope you like the idea and enjoy the video!
The screenshot from the demo video
Demo video: https://youtu.be/Op4QRTJOGMY
More details here: https://arxiv.org/abs/2203.04927
submitted by /u/Kanahei
[link] [comments]
( 1
min )
deepmind/mctx: Monte Carlo tree search in JAX (github.com)
submitted by /u/jack281291
[link] [comments]
( 1
min )
submitted by /u/your_kompanions
[link] [comments]
In December 2020, AWS announced the general availability of Amazon SageMaker JumpStart, a capability of Amazon SageMaker that helps you quickly and easily get started with machine learning (ML). JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as well as a selection of end-to-end solutions that […]
( 9
min )
MLK Visiting Professor S. Craig Watkins looks beyond algorithm bias to an AI future where models more effectively deal with systemic inequality.
( 5
min )
For context, I am a cofounder of Encord, a company building software to improve training data for computer vision.
( 6
min )
Hey everyone!
We just posted Part 2 of our Tutorial on Conformal Prediction and Distribution-Free Uncertainty Quantification on YouTube!
https://youtu.be/TRx4a2u-j7M
It focuses on conditional coverage and diagnostics to make sure your conformal procedure is working properly. It's slightly more advanced than the last one, but will leave you with a strong understanding of how to implement/evaluate conformal in code.
Let us know if you have any feedback by shooting me an email :)
Best,
Anastasios
submitted by /u/aangelopoulos
[link] [comments]
( 1
min )
Wednesday night (3/16), 8-11 pm EDT, FSU professor and computer scientist Dr. Chris Mills will be the guest on Ask_a_Scientist_Gaming.
Chris’ research focus started in applications of machine learning to common software development tasks like concept location and traceability link recovery but has since broadened to applications of machine learning across many industries including finance and law. Current projects include building database-agnostic, natural language interfaces for question-and-answer systems with impedance reduction built from off-the-shelf object-relational mapping. With such an interface, users can directly answer questions and query data with no knowledge of a query language and no need to have custom reports constructed for each information need. Think “Jarvis,” but employees play the role of Iron Man at a bank… and a law firm…. and a hospital… and a university…. and the list goes on.
If you can’t make the live stream, feel free to leave your question in the comments and we will get them answered. Then follow up with our YouTube channel where we will post the video.
submitted by /u/HansonFSU
[link] [comments]
( 1
min )
submitted by /u/nick7566
[link] [comments]
submitted by /u/Recent_Coffee_2551
[link] [comments]
submitted by /u/limapedro
[link] [comments]
( 1
min )
submitted by /u/mr-minion
[link] [comments]
( 1
min )
submitted by /u/Afkfish
[link] [comments]
submitted by /u/dannylenwinn
[link] [comments]
submitted by /u/trcytony
[link] [comments]
Organizations use messaging platforms like Slack to bring the right people together to securely communicate with each other and collaborate to get work done. A Slack workspace captures invaluable organizational knowledge in the form of the information that flows through it as the users collaborate. However, making this knowledge easily and securely available to users […]
( 6
min )
Critical information can be scattered across multiple data sources in your organization, including sources such as Windows file systems stored on Amazon FSx for Windows File Server. You can now use the Amazon Kendra connector for FSx for Windows File Server to index documents (HTML, PDF, MS Word, MS PowerPoint, and plain text) stored in […]
( 8
min )
In this post, we demonstrate how to create an automated email response solution using Amazon Comprehend. Organizations spend lots of resources, effort, and money on running their customer care operations to answer customer questions and provide solutions. Your customers may ask questions via various channels, such as email, chat, or phone, and deploying a workforce […]
( 5
min )
We’ve released new versions of GPT-3 and Codex which can edit or insert content into existing text, rather than just completing existing text. These new capabilities make it practical to use the OpenAI API to revise existing content, such as rewriting a paragraph of text or refactoring code.
( 13
min )
Calculus for Machine Learning Crash Course. Get familiar with the calculus techniques in machine learning in 7 days. Calculus is […]
The post Calculus for Machine Learning (7-day mini-course) appeared first on Machine Learning Mastery.
( 18
min )
submitted by /u/mr-minion
[link] [comments]
( 1
min )
I blew it last week. I’ll readily admit it. Blame it on the flu or Covid or whatever the nasty bug was that confined me to bed for a day and fuzzy for a few. It’s not often that the 15th of March happens to come up on the same day as the weekly newsletter… Read More »DSC Weekly Digest 15 March 2022: Beware the Ides of …
The post DSC Weekly Digest 15 March 2022: Beware the Ides of … appeared first on Data Science Central.
( 4
min )
What is Data Fabric ?
( 2
min )
A machine-learning model for image classification that’s trained using synthetic data can rival one trained on the real thing, a study shows.
( 6
min )
submitted by /u/gwern
[link] [comments]
( 1
min )
submitted by /u/hardmaru
[link] [comments]
Made a super tiny library that hashes your data and compares the hashes to determine if you have samples leaked into the other dataset.
Main usage is to add one line of code before your training loop as an extra check.
Useage is as easy as: python spills = check_spill(train_loader, test_loader)
Github: https://github.com/LaihoE/did-it-spill Currently only for PyTorch
submitted by /u/yliopisto420
[link] [comments]
( 2
min )
submitted by /u/notrealAI
[link] [comments]
Hi folks,
SuperAnnotate is launching webinar series on automated computer vision pipelines, and the first episode is here for you to check out!
submitted by /u/WeekendClassic
[link] [comments]
submitted by /u/bendee983
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/cookingandcraft
[link] [comments]
This is a post co-written with Bernard Paques, CTO of Storm Reply, and Karl Herkt, Senior Strategist at Dassault Systèmes 3DExcite. While computer vision can be crucial to industrial maintenance, manufacturing, logistics, and consumer applications, its adoption is limited by the manual creation of training datasets. The creation of labeled pictures in an industrial context […]
( 10
min )
Are you aware of the technicalities involved in making Machine Learning models holistic, intuitive, and impactful? If not, you first need…
( 3
min )
submitted by /u/UpperSpecialist6286
[link] [comments]
A considerable part of the population uses mobile devices and computers to search data. They also store and perform data procedures. However, not everyone is aware of the relevance of data backup. Your crucial data is essential for anything that you do. It is here that technical support companies can help. Whether it’s your desktop… Read More »Why is Data Back-Up Necessary? The Benefits of Availing Technical Support
The post Why is Data Back-Up Necessary? The Benefits of Availing Technical Support appeared first on Data Science Central.
( 3
min )
In the past, Metadata Management is used to know how to use data catalog to find simple data or a book or a periodical in a library. However, today it is one of the most critical data practices for a successful organization dealing with data. With the rise of distributed architectures, including cloud & big… Read More »Why do you need a metadata management system? Definition and Benefits.
The post Why do you need a metadata management system? Definition and Benefits. appeared first on Data Science Central.
( 3
min )
Just wanted to ask anyone with experience working in the field of implicit neural represenations regarding the compute requirements you've experienced when developing models. Mainly looking in the domain of neural radiance fields (https://www.matthewtancik.com/nerf). I do have cluster access for evaluating projects that are more mature in the development pipeline, but wanted to gauge if anyone had any advice regarding what has worked when still in earlier development mainly when working on my standalone PC.
Thanks so much for any help!
submitted by /u/Ungreon
[link] [comments]
( 1
min )
A well popularized article in Quanta magazine ask the question « Will Transformers Take Over Artificial Intelligence? ». Since having revolutionized NLP, attention is conquering computer vision and reinforcement learning. I find pretty unfortunate that the attention mechanism was totally eclipsed by Transformers which is just a funny name (animation movie/ toy) for self-attention architecture, although the Google's paper title on Transformers was «Attention is all you need».
submitted by /u/ClaudeCoulombe
[link] [comments]
( 1
min )
submitted by /u/meldiwin
[link] [comments]
( 2
min )
submitted by /u/kris33
[link] [comments]
submitted by /u/Thenamessd
[link] [comments]
Ice protects the Earth layer and its oceans by acting as a shield. Excess heat is reflected into space by these dazzling white spots, keeping the Earth cold. Many glaciers throughout the world have been melting quickly since the early 1900s. Human actions cause this phenomenon. Carbon dioxide (CO2) and other greenhouse gas emissions have elevated temperatures since the industrial revolution.
Melting glaciers are a contributing factor in rising sea levels, which leads to an increase of coastal erosion and storm surge. Warmer air temperatures lead directly into more frequent storms like hurricanes or typhoons with stronger winds that cause even greater damage on land. Many cities are already planning to deal with long-term flooding, which may carry salt and moisture into houses and infrastructure, jeopardize drinking water and agriculture, and severely damaged ports.
Given the gravity of the problem, it is critical to understand how much and how quickly sea levels will rise. The projections in the existing predictive models made by scientists are pretty uncertain. Since the contribution from the southernmost continent is so unknown, governments worldwide must consider an unlimited number of scenarios when planning for the future.
A group of Stanford University scientists employed autonomous drone technology and machine learning approach to focus their efforts on discovering and gathering the most valuable data in Antarctica to increase our understanding of the processes that drive sea-level rise.
Continue Reading Our Summary on This Research From Stanford or checkout the HAI Report
submitted by /u/No_Coffee_4638
[link] [comments]
( 1
min )
Hey My Reddit Fellows,
I just wanted to share a video series I am making about AGI, how to manage AGI Safety, and what the post singularity society will look like. Please subscribe to my channel, and let me know if you have any feedback and what topics you would like to see next!
►Playlist: https://youtube.com/playlist?list=PLb4nW1gtGNse4PA_T4FlgzU0otEfpB1q1
►AGI Existential Threat: https://youtu.be/V4iQP7VDMvI
►Life 3.0: https://youtu.be/aWlSwZKzmzY
►Dangers of AGI Sub Goals: https://youtu.be/_-tQH03rq4g
►How to Create an AGI: https://youtu.be/7OHhqli9oaA
Thank you!
Bill
submitted by /u/billgggggg
[link] [comments]
( 2
min )
submitted by /u/crazygrumpy
[link] [comments]
submitted by /u/kris33
[link] [comments]
submitted by /u/Wiskkey
[link] [comments]
I recently had a long conversation with Tim Scarfe and Keith Duggar on Machine Learning Street Talk (MLST) about theory related to neural networks. I really believe we can make better machine learning algorithms and better guarantees if we uncover the right theoretical track. I would really appreciate hearing from you all in the community about this work, so I've written up this post to accompany the MLST video. Enjoy!
See the full interactive version of this post on my research page here.
Get the code for these experiments here.
Data Distributions and Initializing Neural Networks
Is it possible for us to make fixed-size multilayer perceptrons (MLP's) provably converge? It's been bothering me that initialization seems arbitrary and all the optimization algorithms produce different resu…
( 4
min )
submitted by /u/filt_er
[link] [comments]
( 3
min )
https://nn.labml.ai/transformers/retro/model.html
This is an annotated (side-by-side notes) implementation of RETRO in PyTorch.
Retrieval Enhanced Transformer (RETRO) is 25X smaller than GPT-3 but has comparable performance. It uses chunks of similar text retrieved based on a frozen BERT model from a massive database (5 trillion tokens) to improve the performance of the model. Since the model can retrieve information from this large database it doesn't have to contain all the facts in the model weights.
submitted by /u/mlvpj
[link] [comments]
( 1
min )
The news was announced here.
submitted by /u/Wiskkey
[link] [comments]
( 1
min )
submitted by /u/Illustrious_Row_9971
[link] [comments]
( 2
min )
Hi folks. I'm a new DL researcher who just began working at a startup that focuses on AI-based drug discovery. I'm afraid this is not the most suitable place to post this since this is more of an engineering idea, but I wanted to hear what you guys think about it and if you have any idea.
I don't know how many of you have encountered the same efficiency issue before, but I've repeatedly come across this theme while implementing my research ideas:
I have a dataset that consists of datapoints with non-uniform length along some dimensions (number of atoms in a molecule, number of amino acids in a protein etc.), and I want to perform numerical calculations (e.g. feed into a DL model) on a tensorized-batched form of them. The batching (turning them into a single tensor) would be an indispensi…
( 4
min )
submitted by /u/sivasiriyapureddy
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/MLtinkerer
[link] [comments]
( 1
min )
submitted by /u/Professional_Card176
[link] [comments]
submitted by /u/binaryfor
[link] [comments]
submitted by /u/ma7modbasha
[link] [comments]
( 2
min )
Scientists conduct trial and error procedures which experimenting, that many times lear to freat scientific breakthroughs. Similarly, foundational research provides for developing large-scale AI systems theoretical insights that reduce the amount of trial and error required and can be very cost-effective.
Microsoft team tunes massive neural networks that are too expensive to train several times. For this, they employed a specific parameterization that maintains appropriate hyperparameters across varied model sizes. The used µ-Parametrization (or µP, pronounced “myu-P”) is a unique way to learn all features in the infinite-width limit. The researchers collaborated with the OpenAI team to test the method’s practical benefit on various realistic cases.
Studies have shown that training large neural networks because their behavior changes as they grow in size are uncertain. Many works suggest heuristics that attempt to maintain consistency in the activation scales at initialization. However, as training progresses, this uniformity breaks off at various model widths.
CONTINUE READING MY SUMMARY ON THIS RESEARCH
Paper: https://www.microsoft.com/en-us/research/uploads/prod/2021/11/TP5.pdf
Github:https://github.com/microsoft/mup
https://i.redd.it/wu93hpd7wvm81.gif
submitted by /u/No_Coffee_4638
[link] [comments]
( 1
min )
Dears.
I have more than 5 years experience in machine learning and deep learning and recently have created a Youtube channel. https://www.youtube.com/channel/UCn9Rujwh7SfHF2RRvy_ks-g In the channel, I first explain a paper, then I implement/explain the code .
Please join, leave a comment, and share with your friends. You can also suggest any paper and I will add it to my list.
I am constantly trying to improve contents and quality.
Thanks.
submitted by /u/MRMohebian
[link] [comments]
( 1
min )
https://pytorch.org/blog/pytorch-1.11-released/
As a longtime TensorFlow user I've been meaning to switch to either JAX or PyTorch, thus I'm pretty intrigued by this.
In the past I've been having a hard time giving up tf.data's pretty elegant fluent interface for performant I/O and data preprocessing. Has anyone tried the new PyTorch equivalent? How does TorchData stack up?
And are there more things in JAX that functorch cannot express or will both autograd engines hit feature parity now-ish?
submitted by /u/carlthome
[link] [comments]
( 1
min )
submitted by /u/nickb
[link] [comments]
submitted by /u/hotcodist
[link] [comments]
submitted by /u/regalalgorithm
[link] [comments]
submitted by /u/OnlyProggingForFun
[link] [comments]
submitted by /u/grumpyfrench
[link] [comments]
( 2
min )
submitted by /u/Recent_Coffee_2551
[link] [comments]
Check to understand how image recognition technology works and why image detection revolutionizes business.
( 8
min )
Chemical engineers use neural networks to discover the properties of metal-organic frameworks, for catalysis and other applications.
( 6
min )
submitted by /u/dwightschrute1905
[link] [comments]
We’ve recently launched our machine learning profiler https://github.com/graphsignal/graphsignal to make ML profiling simple and usable. It automatically provides operation and kernel level statistics as well as detailed resource usage information necessary for making training and inference faster and more efficient.
More details and screenshots in the blog post https://graphsignal.com/blog/machine-learning-profiler-for-training-and-inference/.
I hope some of you find it useful. Any feedback is appreciated.
submitted by /u/l0g1cs
[link] [comments]
( 1
min )
Deep Learning Is Hitting a Wall: What would it take for artificial intelligence to make real progress?
Essay by Gary Marcus, published on March 10, 2022 in Nautilus Magazine.
Link to the article: https://nautil.us/deep-learning-is-hitting-a-wall-14467/
submitted by /u/hardmaru
[link] [comments]
( 4
min )
submitted by /u/kuasha7
[link] [comments]
submitted by /u/mgalarny
[link] [comments]
For the 14th consecutive year, each Academy Award nominee for the Best Visual Effects used NVIDIA technologies. The 94th annual Academy Awards ceremony, taking place Sunday, March 27, has five nominees in the running: Dune Free Guy No Time to Die Shang-Chi and the Legend of the Ten Rings Spider-Man: No Way Home NVIDIA has Read article >
The post At the Movies: For 14th Year Running, NVIDIA Technologies Power All VFX Oscar Nominees appeared first on NVIDIA Blog.
( 4
min )
Say hello to tomorrow’s smart electric meter, literally. You can ask some next-generation home energy hubs questions, just like you do Alexa or Siri. Some devices, arriving this year, will display real-time simulations — vibrant as a video game — to show how you can lower your energy bill or reduce your carbon footprint. They’ll Read article >
The post Light Me Up: Innovators Redefine Energy Meters for a More Efficient Grid appeared first on NVIDIA Blog.
( 5
min )
The GeForce NOW RTX 3080 membership gives gamers unrivaled performance from the cloud – with latency so low that it feels just like playing on a local PC. Today, gamers can experience RTX 3080-class streaming at only $19.99 a month, thanks to GeForce NOW’s new monthly membership plans*. It’s a great chance to experience powerful Read article >
The post GeForce NOW RTX 3080 One-Month Memberships Now Available appeared first on NVIDIA Blog.
( 3
min )
In this post, we will demonstrate how to securely launch notebook instances in a private subnet of an Amazon Virtual Private Cloud (Amazon VPC), with internet access disabled, and to securely connect to Amazon Simple Storage Service (Amazon S3) using VPC endpoints. This post is for network and security architects that support decentralized data science […]
( 9
min )
Many software as a service (SaaS) providers across various industries are adding machine learning (ML) and artificial intelligence (AI) capabilities to their SaaS offerings to address use cases like personalized product recommendation, fraud detection, and accurate demand protection. Some SaaS providers want to build such ML and AI capabilities themselves and deploy them in a […]
( 14
min )
Amazon SageMaker Autopilot is an automated machine learning (AutoML) solution that performs all the tasks you need to complete an end-to-end machine learning (ML) workflow. It explores and prepares your data, applies different algorithms to generate a model, and transparently provides model insights and explainability reports to help you interpret the results. Autopilot can also […]
( 8
min )
In this post, we present a solution for digitizing transactional documents using Amazon Textract and incorporate a human review using Amazon Augmented AI (A2I). You can find the solution source at our GitHub repository. Organizations must frequently process scanned transactional documents with structured text so they can perform operations such as fraud detection or financial […]
( 7
min )
submitted by /u/mr-minion
[link] [comments]
( 1
min )
AWESOME MACHINE LEARNING
( 3
min )
It is no secret that a mobile app is among the most powerful tools at the disposal of the market and that too across all sectors. They not only empower companies with the ability to reach out to and engage with their customers all over the world but also deliver a powerful boost to their… Read More »Flutter vs Kotlin: Comparison of Mobile App Development Frameworks
The post Flutter vs Kotlin: Comparison of Mobile App Development Frameworks appeared first on Data Science Central.
( 3
min )
Looking to fill open tech positions with quality hires quickly? Like many other IT leaders, you may be facing the uphill task of finding skilled candidates for various tech positions. A report on the impact of technology predicts that in 2022, filling tech positions will remain the key challenge for 73 percent of IT leaders.… Read More »Fast-track The Way You Find Tech Talent with These IT Staffing Solutions
The post Fast-track The Way You Find Tech Talent with These IT Staffing Solutions appeared first on Data Science Central.
( 4
min )
Data management (DM) discussions can be frustrating because both those feeling the pain and the consultants who try to help them are–90+ percent of the time, it seems–still using the same old ways. Those ways only go so far, and won’t go any farther. That’s because those who reinforce the old ways assume that what… Read More »The long game: Desiloed systems and feedback loops by design (I of II)
The post The long game: Desiloed systems and feedback loops by design (I of II) appeared first on Data Science Central.
( 5
min )
Projects fail. There are many reasons why they do, but a surprising number of them come down to one or more variations of the “Wishful Thinking” theme. From a data science standpoint, this is usually referred to as making faulty assumptions, but the idea is the same. And with very few exceptions, the assumptions being… Read More »DSC Weekly Digest 08 March 2022: Beware of Wishful Thinking
The post DSC Weekly Digest 08 March 2022: Beware of Wishful Thinking appeared first on Data Science Central.
( 5
min )
submitted by /u/Kagermanov
[link] [comments]
submitted by /u/nick7566
[link] [comments]
See here for info.
submitted by /u/UnityPlum
[link] [comments]
submitted by /u/harshsharma9619
[link] [comments]
submitted by /u/frog9913
[link] [comments]
This guide is intended for anyone having zero or a small background in programming, maths, and machine learning. There is no specific order to follow, but a classic path would be from top to bottom. If you don't like reading books, skip it, if you don't want to follow an online course, you can skip it as well. There is not a single way to become a machine learning expert and with motivation, you can absolutely achieve it.
The video: https://youtu.be/RirEw-uaS_8?list=PLO4GrDnQanVfb6Ins6up1xScJHl8YuwPQ
The complete article: https://pub.towardsai.net/start-machine-learning-in-2020-become-an-expert-from-nothing-for-free-f31587630cf7
All the links on GitHub: https://github.com/louisfb01/start-machine-learning-in-2020
Artificial is a fantastic field, but it goes extremely fast. Don't miss out on the most important and exciting news by joining great communities, people, newsletters, and more you can all find in this guide!
submitted by /u/OnlyProggingForFun
[link] [comments]
( 1
min )
submitted by /u/dannylenwinn
[link] [comments]
( 1
min )
submitted by /u/dwightschrute1905
[link] [comments]
( 1
min )
Amazon Comprehend is a natural language processing (NLP) service that uses machine learning (ML) to discover insights from text. As a fully managed service, Amazon Comprehend requires no ML expertise and can scale to large volumes of data. Amazon Comprehend provides several different APIs to easily integrate NLP into your applications. You can simply call […]
( 8
min )
Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning (ML) models based on your data, while allowing you to maintain full control and visibility. We have recently announced support for time series data in Autopilot. You can use Autopilot to tackle regression and classification tasks on time series data, or sequence data […]
( 5
min )
This is a guest post by Oliver Frost, data scientist at ImmoScout24, in partnership with Lukas Müller, AWS Solutions Architect. In 2010, ImmoScout24 released a price index for residential real estate in Germany: the IMX. It was based on ImmoScout24 listings. Besides the price, listings typically contain a lot of specific information such as the […]
( 12
min )
This post is authored by Satish Jha, Intelligent Automation Manager, Matt Docherty, Data Science Manager, Jayesh Muley, Associate Consultant and Tapan Vora, Rapid Prototyping, from ZS Associates. At ZS Associates, we do a significant amount of qualitative market research. The work involves interviewing relevant subjects (such as healthcare professionals and sales representatives) and developing bespoke […]
( 7
min )
Hey, machine learning experts!
I represent a community-driven open source project called MindsDB (see on GitHub). We need your feedback about our concept for doing machine learning using SQL! It is called AI Tables and aims to democratize machine learning for all who work with data. There's an article on Medium with SQL commands examples.
Please share your thoughts about it. Your true opinions will be a great contribution towards what a team of 25+ people are working on in the last 3 years!
Thanks in advance!
Costa
submitted by /u/C0staTin
[link] [comments]
( 1
min )
The report[https://www.theverge.com/2017/12/5/16737224/global-ai-talent-shortfall-tencent-report] by The Verge says "Tencent says there are only 300,000 AI engineers worldwide in 2017", Personally, I'm curious how many machine learning engineers in 2022, anyone have any idea?
submitted by /u/joeytai1997
[link] [comments]
( 1
min )
submitted by /u/nickb
[link] [comments]
submitted by /u/mr-minion
[link] [comments]
( 1
min )
WHAT IS HUMAN-MACHINE INTERFACE (HMI)?
( 1
min )
https://youtu.be/6dvcYx9hcbE
This is an in-depth paper review, followed by an interview with the papers' authors!
Society is ruled by norms, and most of these norms are very useful, such as washing your hands before cooking. However, there also exist plenty of social norms which are essentially arbitrary, such as what hairstyles are acceptable, or what words are rude. These are called "silly rules". This paper uses multi-agent reinforcement learning to investigate why such silly rules exist. Their results indicate a plausible mechanism, by which the existence of silly rules drastically speeds up the agents' acquisition of the skill of enforcing rules, which generalizes well, and therefore a society that has silly rules will be better at enforcing rules in general, leading to faster adapt…
( 2
min )
Video #1
Video #2
Video #3
Video #4
View Poll
submitted by /u/Recent_Coffee_2551
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/doctanonymous
[link] [comments]
submitted by /u/sivasiriyapureddy
[link] [comments]
submitted by /u/tortadinuvole
[link] [comments]
submitted by /u/Recent_Coffee_2551
[link] [comments]
submitted by /u/Thenamessd
[link] [comments]
submitted by /u/Recent_Coffee_2551
[link] [comments]
( 1
min )
submitted by /u/bent_out_of_shape_
[link] [comments]
submitted by /u/urocyon_dev
[link] [comments]
This is a guest post authored by Andrew Masek, Software Engineer at The Barcode Registry and Erik Quisling, CEO of The Barcode Registry. Product counterfeiting is the single largest criminal enterprise in the world. Growing over 10,000% in the last two decades, sales of counterfeit goods now total $1.7 trillion per year worldwide, which is […]
( 6
min )
🔥 I received several messages about the benefits of joining FAANG and similar companies and startups in the context of Data Science…
( 2
min )
submitted by /u/urocyon_dev
[link] [comments]
submitted by /u/givdwiel
[link] [comments]
( 1
min )
If you want to help make a difference in the world, we are looking for collaborators in a unique study of butterflies.
In collaboration with Zooniverse and Microsoft’s AI for Earth. We’re using artificial intelligence to extract wing traits from millions of digitized museum specimens. Wing size and color are important for thermoregulation, dispersal ability, and thus responses to land use and climate change.
The integration of emerging technology with digitization of museum specimens around the world opens up new and exciting research questions.
Join the mission.
https://collaboratory.ist/job/ai-for-butterflies.html/
submitted by /u/tsunamisweetpotato
[link] [comments]
( 1
min )
Ever wondered how OCR engines extract information, and structure it? Here is an explainer on one of the most successful deep learning models that is able to achieve this. https://nanonets.com/blog/layoutlm-explained/
submitted by /u/ze_mle
[link] [comments]
This article focuses on what is happening behind the execution of a Tensor in the deep learning framework OneFlow. It takes the operator oneflow.relu as an example to introduce the Interpreter and VM mechanisms that need to be relied on to execute this operator.
article: https://oneflow2020.medium.com/the-execution-process-of-a-tensor-in-a-deep-learning-framework-a4d853645d5b
submitted by /u/Just0by
[link] [comments]
( 1
min )
For more information, https://stackoverflow.com/questions/71387216/how-do-i-train-a-from-scratch-image-recognition-neural-network.
submitted by /u/UnityPlum
[link] [comments]
submitted by /u/regalalgorithm
[link] [comments]
( 1
min )
submitted by /u/bendee983
[link] [comments]
submitted by /u/Visionifyai
[link] [comments]
submitted by /u/Recent_Coffee_2551
[link] [comments]
Hey My Reddit Fellows,
I just wanted to share a video series I am making about AGI, how to manage AGI Safety, and what the post singularity society will look like. I am looking to help share some of the most important thoughts from AI safety experts to ensure that current ML practitioners and next generation will have the important knowledge to build a path to a prosperous future together. Please check it out, subscribe to my channel, and let me know if you have any feedback and what topics you would like to see next!
https://youtube.com/playlist?list=PLb4nW1gtGNse4PA_T4FlgzU0otEfpB1q1
AGI Existential Threat: https://youtu.be/V4iQP7VDMvI
Life 3.0: https://youtu.be/aWlSwZKzmzY
Dangers of AGI Sub Goals: https://youtu.be/_-tQH03rq4g
How to Create an AGI: https://youtu.be/7OHhqli9oaA
Thank you!
Bill
submitted by /u/billgggggg
[link] [comments]
( 1
min )
Moving enterprise content management to the cloud comes with impressive business benefits — operating costs are reduced, capital…
( 3
min )
What is Deep Learning ?
( 3
min )
In part 1: A gentle introduction to positional encoding in transformer models, we discussed the positional encoding layer of the […]
The post The Transformer Positional Encoding Layer in Keras, Part 2 appeared first on Machine Learning Mastery.
( 9
min )
submitted by /u/Ok_Can2425
[link] [comments]
( 1
min )
submitted by /u/pinter69
[link] [comments]
( 1
min )
submitted by /u/Illustrious_Row_9971
[link] [comments]
( 2
min )
submitted by /u/giugiacaglia
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
I wrote a step-wise tutorial to demonstrate the steps required to deploy an ML model using GCP's Google AI Platform and using Streamlit to access the model API through a UI.
Check out the blog here - https://shreyansh26.github.io/post/2022-03-06_model_deployment_using_gcp_google_ai_platform/
submitted by /u/shreyansh26
[link] [comments]
submitted by /u/getrich_or_diemining
[link] [comments]
( 1
min )
submitted by /u/glenniszen
[link] [comments]
( 1
min )
Machine learning (ML) is becoming a more critical application for developers since it allows them to train models that can do various prediction-based activities. You may have had to develop a complicated rules engine in the past, relying on mathematical methodologies to offer the essential statistical models.
Predictions are what we call machine learning (ML) outputs, although they may be anything. They can be detected items if you use computer vision. They’re intent or translations if you’re utilizing a language model. Whatever the result, it’s a statistically weighted answer with a confidence level that may be used to verify any results.
Working with machine learning has two components. If you have a prebuilt model, you may use a REST API to interact with its predictions on a cloud platform like Azure ML or export it in the widely accepted ONNX (Open Neural Network Exchange) format and run it on a PC using tools like WinML. That’s the simple part; training and evaluating a model is complex. That method necessitates a large amount of data to be verified and tagged. Also, there is a substantial amount of computing on a CPU or on a GPGPU (general-purpose GPU).
Continue Reading My Summary on PyTorch-DirectML Release-2
Download: https://pypi.org/project/pytorch-directml/
Github: https://github.com/microsoft/DirectML
submitted by /u/No_Coffee_4638
[link] [comments]
( 1
min )
What would an AI who's never seen or heard of golf courses do when shown a list of real golf course names and challenged to generate more?
When Jeff Kissel sent me 15,626 existing golf course names from the National Course Rating Database, I thought I might
( 3
min )
AI Weirdness: the strange side of machine learning
( 1
min )
submitted by /u/neuronovesite_cz
[link] [comments]
About a year ago, I started the pianist AI project with the aim of having an AI model that can generate piano pieces. Although the optimization is still in process, today, finally it seems the model has learned the basic concepts.
I have named the first piece of Level 7: Peace> https://youtu.be/rLW3KwCG41M
With the hope of better tomorrow….
submitted by /u/amin_mlm
[link] [comments]
( 1
min )
submitted by /u/Just0by
[link] [comments]
( 1
min )
Deep generative models have produced realistic samples in a variety of domains, including image and audio. Video generation has recently emerged as the next issue for deep generative models, prompting a long line of research to learn video distribution.
Despite their efforts, there is still a big gap between large-scale real-world recordings and simulations. The intricacy of video signals, which are continuously coupled across spatiotemporal directions, contributes to the difficulty of video creation. Specifically, most previous works have modeled the video as a 3D grid of RGB values, i.e., a succession of 2D images, using discrete decoders such as convolutional or autoregressive networks. However, because of the cubic complexity, such discrete modeling limits the scalability of created movies and misses the intrinsic continuous temporal dynamics.
Continue Reading My Article Summary On This Research
Paper: https://openreview.net/pdf?id=Czsdv-S4-w9
Github: https://github.com/sihyun-yu/digan
Project: https://sihyun-yu.github.io/digan/
https://reddit.com/link/t7f7ti/video/nicll8ujvll81/player
submitted by /u/No_Coffee_4638
[link] [comments]
( 1
min )
submitted by /u/OnlyProggingForFun
[link] [comments]
submitted by /u/MarS_0ne
[link] [comments]
submitted by /u/giugiacaglia
[link] [comments]
submitted by /u/hardmaru
[link] [comments]
submitted by /u/crp1994
[link] [comments]
( 2
min )
submitted by /u/Recent_Coffee_2551
[link] [comments]
submitted by /u/mihircontra20
[link] [comments]
submitted by /u/bigdataengineer4life
[link] [comments]
submitted by /u/Thenamessd
[link] [comments]
This is part 1 in a multi-part series on the value-realizing, collaborative power of decisions. My mom used to say, “If it was a snake, you’d be dead”. And the reason that I say that, is that organizations are seeking a collaborative value driver that can 1) align the organization around the economic power of… Read More »Decisions Part 1: Creating an AI-driven Decision Factory
The post Decisions Part 1: Creating an AI-driven Decision Factory appeared first on Data Science Central.
( 5
min )
Hello everyone. I am excited about the invitation to do an AMA here. It's my first AMA on reddit, and I will be trying my best! I recently wrote the "Machine Learning with Pytorch and Scikit-Learn" book and joined a startup(Grid.ai) in January. I am also an Assistant Professor of Statistics at the University of Wisconsin-Madison since 2018. Btw. I am also a very passionate Python programmer and love open source.
Please feel free to ask me anything about my book, working in industry (although my experience is still limited, haha), academia, or my research projects. But also don't hesitate to go on tangents and ask about other things -- this is an ask me anything after all (... topics like cross-country skiing come to mind).
EDIT:
Thanks everyone for making my first AMA here a really fun experience! Unfortunately, I have to call it a day, but I had a good time! Thanks for all the good questions, and sorry that I couldn't get to all of them!
submitted by /u/seraschka
[link] [comments]
( 9
min )
MEng graduate students engage with IBM to develop their research skills and solutions to real-world problems.
( 6
min )
Whether you’re allocating resources more efficiently for web traffic, forecasting patient demand for staffing needs, or anticipating sales of a company’s products, forecasting is an essential tool across many businesses. One particular use case, known as cold start forecasting, builds forecasts for a time series that has little or no existing historical data, such as […]
( 6
min )
Real estate businesses have existed for many years and will almost definitely continue to succeed.
( 4
min )
The deployment of powerful AI systems has enriched our understanding of safety and misuse far more than would have been possible through research alone. Notably:
API-based language model misuse often comes in different forms than we feared most.
We have identified limitations in existing language model evaluations that we are
( 9
min )
Call for expressions of interest to study the economic impacts of Codex.
( 4
min )
submitted by /u/gwern
[link] [comments]
https://www.immunai.com/press/advancements-in-gene-regulatory-networks-immunais-third-symposium
submitted by /u/pahita
[link] [comments]
( 1
min )
We have two talks next week (week of 7 Mar.) for our upcoming webinar series about the intersection of Bayesian inference and causal inference. Our speakers will help us understand how we can use these two frameworks in order to solve applied problems, and will consider if these different frameworks are in conflict or are complimentary. The intended audience is machine learning practitioners and statisticians from academia and industry.
Upcoming talks, with Zoom registration links:
7 March
Andrew Gelman - Bayesian Methods in Causal Inference and Decision Making
Consider the problem of A/B testing (that is, an experiment or observational study designed to estimate the effect of some exposure or treatment). The basic data analysis workflow is to start by comparing the average outcomes…
( 1
min )
submitted by /u/hardmaru
[link] [comments]
submitted by /u/ObjectiveGround5
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
( 1
min )
submitted by /u/HumanSeeing
[link] [comments]
( 1
min )
submitted by /u/LifeSymbiont
[link] [comments]
A new MIT-wide effort launched by the Institute for Data, Systems, and Society uses social science and computation to address systemic racism.
( 5
min )
At the 2021 AWS re:Invent conference in Las Vegas, we demoed Read For Me at the AWS Builders Fair—a website that helps the visually impaired hear documents. For better quality, view the video here. Adaptive technology and accessibility features are often expensive, if they’re available at all. Audio books help the visually impaired read. Audio […]
( 7
min )
A new month means a whole new set of games coming to GeForce NOW. Members can look forward to 27 titles joining the GeForce NOW library in March, including day-and-date releases like Shadow Warrior 3, with support for NVIDIA DLSS. Bring a Katana to a Gunfight Shoot, slash and slide into Shadow Warrior 3, new Read article >
The post GFN Thursday Marches Forward With 27 Games Coming to GeForce NOW This Month appeared first on NVIDIA Blog.
( 3
min )
This is a beefed version of SEER which was released a year ago, scaled from 1B to 10B parameters, showing improved generalization on different tasks.
Also, the self supervised learning (SSL) allowed for a better coverage of the world , thus reducing bias from labelled datasets mostly originating from specific countries (e.g. US).
Results look very nice.
More details in their post.
submitted by /u/k-folder
[link] [comments]
( 1
min )
Hi folks, we recently implemented multi-touch attribution using shapley and markov chain values at our org, and I wrote a blog post about how we implemented it using a mix of tools (primarily dbt, sagemaker, and our internal tools). I am sharing it here hoping people might find it interesting. Do let me know if you have any questions/feedback/suggestions.
https://www.rudderstack.com/blog/from-first-touch-to-multi-touch-attribution-with-rudderstack-dbt-and-sagemaker/
submitted by /u/dileep31
[link] [comments]
( 1
min )
Are there any pytorch libraries to do benchmarking of domain adaptation methods for audio/speech tasks? Something like the Transfer Learning Library (https://github.com/thuml/Transfer-Learning-Library/) for images.
submitted by /u/kiran__chari
[link] [comments]
submitted by /u/Kagermanov
[link] [comments]
submitted by /u/justine01923
[link] [comments]
submitted by /u/thedyezwfl
[link] [comments]
submitted by /u/DaveBowman1975
[link] [comments]
Programming is way more fun when you learn/work with someone. Help each other, ask questions, brainstorm, etc. There is just so much benefit to joining a community when you are in this field, especially when you cannot find the question you are looking for on stack overflow! 😉
This is the same thing with AI, and it is why, nearly two years ago now, we created a Discord server where anyone learning or working in the field could come and share their projects, learn together, work together, and much more. The community has now over 22'000 members, which is just unbelievable! We are so glad to see it growing and especially to see everyone so active.
We would love for anyone to join and exchange with us, especially if you are willing to give some of your precious time to share your knowledge and help other people.
We have special events and projects for the community as well as cool offers and giveaways, such as an NVIDIA RTX 3080Ti giveaway running right now in collaboration with NVIDIA for the GTC event for the community members! (check out the #announcement channel for more information about this ;) )
Come join us if you are in the field of AI !
https://discord.gg/learnaitogether
submitted by /u/OnlyProggingForFun
[link] [comments]
( 1
min )
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/nousetest
[link] [comments]
Imagine walking through the bustling streets of London’s Piccadilly Circus, when suddenly you’re in a tropical rainforest, surrounded by vibrant flowers and dancing butterflies. That’s what audiences will see in the virtual world of The Green Planet AR Experience, an interactive, augmented reality experience that blends physical and digital worlds to connect people with nature. Read article >
The post Beyond Be-leaf: Immersive 3D Experience Transports Audiences to Natural Worlds With Augmented Reality appeared first on NVIDIA Blog.
( 4
min )
The very thing that makes the internet so useful to so many people — the vast quantity of information that’s out there — can also make going online frustrating. There’s so much available that the sheer volume of choices can be overwhelming. That’s where recommender systems come in, explains NVIDIA AI Podcast host Noah Kravitz. Read article >
The post Podsplainer: What’s a Recommender System? NVIDIA’s Even Oldridge Breaks It Down appeared first on NVIDIA Blog.
( 8
min )
The Social and Ethical Responsibilities of Computing publishes a collection of original pedagogical materials developed for instructional use on MIT OpenCourseWare.
( 5
min )
Researchers find similarities between how some computer-vision systems process images and how humans see out of the corners of our eyes.
( 8
min )
In the presence of extrinsic rewards, Deep Reinforcement Learning (RL) is a strong strategy for tackling complex control tasks. Playing video games with pixels, mastering the game of Go, robotic mobility, and dexterous manipulation policies are all examples of successful applications.
While effective, the above advancements resulted in agents that were unable to generalize to new downstream tasks other than the one for which they were trained. Humans and animals, on the other hand, can learn skills and apply them to a range of downstream activities with little supervision. In a recent paper, UC Berkeley researchers aim to teach agents with generalization capabilities by efficiently adapting their skills to downstream tasks.
Continue reading my summary on this paper
Paper | Github
https://preview.redd.it/jeomp8g2d0l81.png?width=1370&format=png&auto=webp&s=24701cfc995eeffcace5a62fb734dce643499487
submitted by /u/No_Coffee_4638
[link] [comments]
( 1
min )
submitted by /u/yazriel0
[link] [comments]
( 1
min )
What is Stroke ?
( 5
min )
The importance of set pieces in football (or soccer in the US) has been on the rise in recent years: now more than one quarter of all goals are scored via set pieces. Free kicks and corners generally create the most promising situations, and some professional teams have even hired specific coaches for those parts […]
( 10
min )
In football, as in many sports, discussions about individual players have always been part of the fun. “Who is the best scorer?” or “Who is the king of defenders?” are questions perennially debated by fans, and social media amplifies this debate. Just consider that Erling Haaland, Robert Lewandowski, and Thomas Müller alone have a combined […]
( 10
min )
How to utilize ML tools for gene regulatory networks and perturbation predictions: https://www.immunai.com/press/advancements-in-gene-regulatory-networks-immunais-third-symposium
submitted by /u/pahita
[link] [comments]
Veritasium posted a great video on the upcoming analog computers being used for neural networks as an alternative to digital computers.
https://www.youtube.com/watch?v=GVsUOuSjvcg&ab_channel=Veritasium
submitted by /u/Random-Machine
[link] [comments]
( 1
min )
Hi everyone!
I created RasgoQL as an open source python package for building dbt-compatible SQL in a pandas-like syntax. It’s already saved me hours of writing CTEs (common table expressions) in SQL, and I hope you’ll give it a try so it can save you time too.
You can check it out here: https://github.com/rasgointelligence/RasgoQL
submitted by /u/p5256
[link] [comments]
( 1
min )
Synthetic datasets are computer-generated samples with the same statistical characteristics as the samples from the original dataset. Synthetic datasets are becoming common to train AIs in areas where real data is scarce or too sensitive to use, as in the case of medical records or personal financial data. I was involved in textual data augmentation for my thesis.
submitted by /u/ClaudeCoulombe
[link] [comments]
( 2
min )
Sponsored Post Me, a data scientist, and Jupyter notebooks. Well, our relationship started back then when I began to learn […]
The post Data Science Notebook Life-Hacks I Learned From Ploomber appeared first on Machine Learning Mastery.
( 5
min )
Serialization refers to the process of converting a data object (e.g. Python objects, Tensorflow models) into a format that allows […]
The post A Gentle Introduction to Serialization for Python appeared first on Machine Learning Mastery.
( 11
min )
We’re moving at the Cagle house and we’re discovering that, after eight years of living at the same place, one family can collect a lot of crap. The issue came up, in discussions with my spouse, that my mother-in-law had no sense of organization — which seemed odd because my wife’s mother was the kind… Read More »DSC Weekly Digest 01 March 2022: Taxonomists Classify, Ontologists Conceptualize
The post DSC Weekly Digest 01 March 2022: Taxonomists Classify, Ontologists Conceptualize appeared first on Data Science Central.
( 6
min )
The last few years have seen rapid development in the field of natural language processing (NLP). While hardware has improved, such as with the latest generation of accelerators from NVIDIA and Amazon, advanced machine learning (ML) practitioners still regularly run into issues scaling their large language models across multiple GPU’s. In this blog post, we […]
( 9
min )
Ambarella builds computer vision SoCs (system on chips) based on a very efficient AI chip architecture and CVflow that provides the Deep Neural Network (DNN) processing required for edge inferencing use cases like intelligent home monitoring and smart surveillance cameras. Developers convert models trained with frameworks (such as TensorFlow or MXNET) to Ambarella CVflow format […]
( 7
min )
Deploying and managing machine learning (ML) models at the edge requires a different set of tools and skillsets as compared to the cloud. This is primarily due to the hardware, software, and networking restrictions at the edge sites. This makes deploying and managing these models more complex. An increasing number of applications, such as industrial […]
( 13
min )
submitted by /u/qptbook
[link] [comments]
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/leonardo-vinci
[link] [comments]
submitted by /u/frog9913
[link] [comments]
submitted by /u/Ziinxx
[link] [comments]
Can something like that be done? For example, the Kaluza-Klein theory was able to derive various existing physic equations using an 5 by 5 matrix. My idea comes from the first 4 minutes of this video https://www.youtube.com/watch?v=mmtLgYVEuJs
submitted by /u/netblazer
[link] [comments]
( 1
min )
GauGAN, an AI demo for photorealistic image generation, allows anyone to create stunning landscapes using generative adversarial networks. Named after post-Impressionist painter Paul Gauguin, it was created by NVIDIA Research and can be experienced free through NVIDIA AI Demos. How to Create With GauGAN The latest version of the demo, GauGAN2, turns any combination of Read article >
The post What Is GauGAN? How AI Turns Your Words and Pictures Into Stunning Art appeared first on NVIDIA Blog.
( 3
min )
Researchers surveyed 100 high-performing companies to determine which of them are leading adopters of machine intelligence and data analytics, and how they succeed.
( 5
min )
A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.
( 7
min )
For anyone curious. Announcement on Twitter: https://twitter.com/sirbayes/status/1498402522511253510
Download link: https://probml.github.io/pml-book/book2.html
submitted by /u/bikeskata
[link] [comments]
Hi, after months of closed beta I'm launching today a free, open source IDE for PyTorch called TorchStudio. It aims to greatly simplify researches and trainings with PyTorch and its ecosystem, so that most tasks can be done visually in a couple clicks. Hope you'll like it, I'm looking forward to feedback and suggestions :)
-> https://torchstudio.ai
submitted by /u/divideconcept
[link] [comments]
( 3
min )
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/bendee983
[link] [comments]
submitted by /u/iamtheoctopus123
[link] [comments]
( 2
min )
submitted by /u/Beautiful-Credit-868
[link] [comments]
submitted by /u/mr-minion
[link] [comments]
( 1
min )
Why do data silos, and now analytic silos, continue to exist? It can’t be due to technical issues. Data silos appeared in the 1990s when we were trying to make Relational Data Base Management Systems (RDMBS) – that were architected for single-record transaction processing – perform massive table scans to identify the trends, patterns, and… Read More »Abundance Mentality is Key to Exploiting the Economics of Data
The post Abundance Mentality is Key to Exploiting the Economics of Data appeared first on Data Science Central.
( 7
min )